uses random selection, every person has equal chance, selection of one person doesn’t interfere with selection of another (put names back in hat after pick)

Stratified random sampling is

divide the population into specific subgroups, or strata, based on a critical characteristic. A set number of research participants are randomly selected from each strata. (can do this proportionally or equally)

Cluster sampling is

sampling unit is a naturally occurring group or clusters of members of the population, instead of sampling individual members you randomly select the clusters

systematic sampling is

sample is drawn by choosing every kth person from a listing of the population (make sure the list is made up randomly)

convenience sampling is

include any participants who are readily available and accessible (not random)

When it comes to questionnaires, what is meant by validity and reliability

Validity: when questionnaire is measuring what is intended to be measured; Reliability: questionnaire measures consistently each time it is used

What are the three ways to establish validity (as discussed in class)?

content-related: experts in field review questionnaire

construct related: use stats approach to be sure I am measuring the construct of (whatever) the whole construct and nothing but the construct

criterion-related: uses two questionnaires. take questionnaire and use stats approach to determine if it correlates with certain criterion (something that theoretically, resilience should be able to predict – like optimism) the take questionnaire and determine using a stats approach if it can distinguish between resilience and something very different (like defeatism)

What are the two ways to establish reliability (as discussed in class)?

- alpha reliability: using stats approach to examine each item on the questionnaire compared with the other items on the questionnaire (most common one)

- test-retest reliability: use statistical approach to examine day-to-day stability of the questionnaire by correlating day 1 scores with day 2 scores (time lapse on this one students take one day and then another day and scores should correlate)

What do the terms statistics mean

values, quantities calculated using info obtained from a sample

What do the terms univariate statistics mean

involves individual variables (meaning one) descriptive statistics are this kind of stats (used to describe and summarize the characteristics of the data from our sample

What do the terms cross-sectional mean

data collected at one point in time

With what type of quantitative research can I use descriptive statistics

all three types descriptive, correlation, experimental

What is a frequency distribution

can be used with either type of data (continuous, categorical) its an ordered listing of the scores and their frequencies

What level of data does my independent variable need to be in a independent groups t test

IV categorical

What level of data does my dependent variable need to be?

DV continuous

What are the two types of independent groups we discussed in class when it comes to independent groups t testing

groups based on existing characteristics (male female); groups based on something I control (teaching method, drug treatment)

When would I use an ANOVA?

compare 3+ independent groups

What level of data does my independent variable need to be? What level of data does my dependent variable need to be in ANOVA

? DV continuous; IV categorical

What do the results of an ANOVA tell you?

tells you there is a statistically significant difference between the three mean scores

What do the ANOVA results not tell you?

doesn’t tell you where the difference lies

What do I need to do to determine where the difference lies between the three groups in my ANOVA?

Post – hoc test

When would I use a Paired Samples t-test?

compare 2 dependent groups

What level of data does my independent variable need to be? What level of data does my dependent variable need to be in a paired samples t test

? IV categorical; DV continuous

What does it mean for groups to be dependent on each other

think pretest postest

When would I use a chi-square?

when you have categorical data. used to determine whether significant differences exist in the number of people who are classified in the categories of the research variables

What is the null hypothesis for a chi-square?

Null: there will be no difference between expected frequencies and observed frequencies

What is the alternative hypothesis in a chi square

Alternative: there will be a difference between expected frequencies and observed frequencies

What level of data do both of my variables need to be in chi square?

categorical

What is the definition of ethics?

morals, norms for conduct that distinguish between acceptable and unacceptable behavior

Why do researchers need to be ethical?

promotes aim of research, promote values essential to collaboration, can be held accountable to the public, promote other moral and social values

What is an Institutional Review Board?

? examines the risks to benefits of proposed reearch studies with respect to protecting human subjects and abiding by federal regulations

How do you define anonymous and confidential

anonymous: inability to link any research information back to the individual respondents;

confidential: ability of researchers to link research information back to the individual respondents but no one else can access the information

What are the key elements of Informed consent?

voluntary no coercion, fully explained expectations described, clear description of risks and benefits, statement indicating anonymous or level of confidentiality indicates who will see the individual results of the participants, participants right to ask any questions any time receive contact info of principal investigator and IRB, statement that participants can withdraw at any time with no consequences

What three actions are considered by the federal government to be research misconduct?

falsification, fabrication, plagiarism

Levenes test for ANOVA

p < .05 you reject the null – assume variances were not equal,

p > .05 you accept the null assume variances were equal

post-hoc test for ANOVA interpret

Use Tukey if equal variances assumed,

use Dunnett if equal variances not assumed (use Levene’s test to find out the variance)

interpret the p-value for the chi-square

If p < .05 reject the null and report that there is a statistically significant difference b/w expected frequencies and observed frequencies ( with this test you hope that the numbers are proportional – which doesn’t’ mean equal numbers at beginning it means proportionate, this is what is meant by expected frequencies)